Angielski
Parallel Processing for Scientific Computing is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, scientists, and computer scientists focus on to make parallel processing effective for scientific problems. It is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth looks at applications that require parallel computing for scaling to solve larger and more realistic models that can advance science and engineering. In sum, this is an up-to-date reference for researchers and application developers on the state of the art in scientific computing. It also serves as an excellent overview and introduction, especially for students interested in computational modeling and simulation.
